Automotive Innovation

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1.

Preface for Feature Topic on Environmentally Benign Automotive Lightweighting

Junying Min, A. Erman Tekkaya, Yongbing Li, Yannis P. Korkolis & Ying Zhao

Automotive Innovation 2023, 6 (3): 297-299. DOI: 10.1007/s42154-023-00236-1

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We organized this Feature Topic and expect it will promote the development of environmentally benign automotive lightweighting technologies and contribute to the “Carbon Net Zero” process. We would also like to take this opportunity to commemorate the Honorary and Founding Executive Editor-in-Chief Professor Fangwu (Mike) Ma for his contributions to eco-driving and for his dedicated support in the publication of the previous Special Issue on Automotive Lightweight in 2020 (https://link.springer.com/journal/42154/volumes-and-issues/3-3).

This Feature Topic comprises eight papers that showcase the latest advances in the pursuit of lightweighting in automotive applications. The core contributions of these articles are summarized below.

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2.

Environmentally Responsible Lightweight Passenger Vehicle Design and Manufacturing

Glenn S. Daehn, Katrin E. Daehn & Oliver Kuttner

Automotive Innovation 2023, 6 (3): 300-210. DOI: 10.1007/s42154-023-00241-4

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The mass reduction of passenger vehicles has been a great focus of academic research and federal policy initiatives of the United States with coordinated funding efforts and even a focus of a Manufacturing USA Institute. The potential benefit of these programs can be described as modest from a societal point of view, for example reducing vehicle mass by up to 25% with modest cost implications (under $5 per pound saved) and the ability to implement with existing manufacturing methods. Much more aggressive reductions in greenhouse gas production are necessary and possible, while delivering the same service. This is demonstrated with a higher-level design thinking exercise on an environmentally responsible lightweight vehicle, leading to the following criteria: lightweight, low aerodynamic drag, long-lived (over 30 years and 2 million miles), adaptable, electric, and used in a shared manner on average over 8 h per day. With these specifications, passenger-mile demand may be met with around 1/10 of the current fleet. Such vehicles would likely have significantly different designs and construction than incumbent automobiles. It is likely future automotive production will be more analogous to current aircraft production with higher costs per pound and lower volumes, but with dramatically reduced financial and environmental cost per passenger mile, with less material per vehicle, and far less material required in the national or worldwide fleets. Subsidiary benefits of this vision include far fewer parking lots, greater accessibility to personal transportation, and improved pedestrian safety, while maintaining a vibrant and engaging economy. The systemic changes to the business models and research and development directions (including lightweight design and manufacturing) are discussed, which could bring forth far more sustainable personal transportation.

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3.

Preface for Cyber-Attack Detection and Resilient Control of Intelligent and Connected Vehicles

Hui Zhang, Manjiang Hu, Anh-Tu Nguyen, Yunpeng Wang & Yang Shi

Automotive Innovation 2023, 6 (2): 143-145. DOI: 10.1007/s42154-023-00227-2

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This Feature Topic brings together experts from the industry and academia to discuss the progress of the latest works on cyber-attack detection and resilient control of ICVs. In this Feature Topic, we have selected four papers among dozens of submissions to showcase the latest research progress. The highlights of these papers are introduced as follows.

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4.

A Double Assessment of Privacy Risks Aboard Top-Selling Cars

Giampaolo Bella · Pietro Biondi · Giuseppe Tudisco

Automotive Innovation 2023, 6 (2): 146-163. DOI: 10.1007/s42154-022-00203-2

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The advanced and personalised experience that modern cars offer makes them more and more data-hungry. For example, the cabin preferences of the possible drivers must be recorded and associated to some identity, while such data could be exploited to deduce sensitive information about the driver’s health. Therefore, drivers’ privacy must be taken seriously, requiring a dedicated risk assessment framework, as presented in this paper through a double assessment combining the asset-oriented ISO approach with the threat-oriented STRIDE approach. The framework is tailored to the level of specific car brand and demonstrated on the ten top-selling brands as well as, due to its innovative character, Tesla. The two approaches yield different, but complementary findings, demonstrating the additional insights gained through their parallel adoption.

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5. Preface for Human-Like Smart Autonomous Driving for Intelligent Vehicles and Transportation Systems

Guofa Li, Cristina Olaverri-Monreal, Houxiang Zhang, Keqiang Li & Paul Green

Automotive Innovation 2023, 6 (1): 1-2. DOI: 10.1007/s42154-023-00217-4

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Drivers are the center of vehicles and transportation systems. Because of the rapid development of advanced technologies, artificial drivers have been developed as key elements in vehicles and transportation systems. The inconsistency between human drivers and artificial drivers will lead to accidents and congestion. To make future vehicles and transportation systems trustworthy in driving safety and acceptable in travel efficiency, developing technologies based on human drivers’ reliable knowledge and cognitive intelligence together with smart operations is an essential and promising solution. However, there are many challenges to be addressed including the learning of smart human perception, reliable smart inference strategies in decision-making, adaptive correction of inappropriate driving operation, knowledge mapping and enhancement of smart human driving in various scenarios, etc.
To alleviate these challenges, emerging technologies inspired by human intelligence (e.g., self-supervised learning, reinforcement learning, game theory, etc.) have been extensively developed in the related communities. This special issue aims to provide a platform for researchers, engineers, and policymakers to share their latest innovative ideas and contributions in developing and applying these novel technologies to address the challenges concerning human-like smart autonomous driving in intelligent vehicles and transportation systems.
Four articles are collected in this feature topic that promotes the recent advances in the field of human-like autonomous driving systems. The feature topic highlights the progress in environment perception, driver behavior analysis, human-vehicle shared control, and decision-making. The core contributions of these four articles are listed below.

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6. Effects of Driver Response Time Under Take-Over Control Based on CAR-ToC Model in Human–Machine Mixed Traffic Flow

Yucheng Zhao, Haoran Geng, Jun Liang, Yafei Wang, Long Chen, Linhao Xu & Wanjia Wang

Automotive Innovation 2023, 6 (1): 3-19. DOI: 10.1007/s42154-022-00207-y

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The take-over control (ToC) of human–machine interaction is a hotspot. From automatic driving to manual driving, some factors affecting driver response time have not been considered in existing models, and little attention has been paid to its effects on mixed traffic flow. This study establishes a ToC model of response based on adaptive control of thought-rational cognitive architecture (CAR-ToC) to investigate the effects of driver response time on traffic flow. A quantification method of driver’s situation cognition uncertainty is also proposed. This method can directly describe the cognitive effect of drivers with different cognitive characteristics on vehicle cluster situations. The results show that when driver response time in ToC is 4.2 s, the traffic state is the best. The greater the response time is, the more obvious the stop-and-go waves exhibit. Besides, crashes happen when manual vehicles hit other types of vehicles in ToC. Effects of driver response time on traffic are illustrated and verified from various aspects. Experiments are designed to verify that road efficiency and safety are increased by using a dynamic take-over strategy. Further, internal causes of effects are revealed and suggestions are discussed for the safety and efficiency of autonomous vehicles.

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7.

Hybrid Adaptive Event-Triggered Platoon Control with Package Dropout

Jiawei Wang, Fangwu Ma, Liang Wu & Guanpu Wu

Automotive Innovation 2022, 5 (4): 347-358. DOI: 10.1007/s42154-022-00193-1

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A novel hybrid adaptive event-triggered platoon control strategy is proposed to achieve the balanced coordination between communication resource utilization and vehicle-following performance considering the effect of package dropout. To deal with the disturbance caused by the event-triggered scheme, the parameter space approach is adopted to derive the feasible region from which cooperative adaptive cruise control controller satisfies internal stability, distance accuracy, and string stability. Subsequently, the Bernoulli random distribution process is employed to depict the phenomenon of package dropout, and the hybrid coefficient is proposed to realize the allocation between the adaptive trigger threshold strategy and the adaptive headway strategy. The simulation of a six-vehicle platoon is carried out to verify the effectiveness of the designed control strategy. Results show that about 78.76% of communication resources have been saved by applying the event-triggered scheme, while guaranteeing the desired vehicle-following performance. And in the non-ideal communication environment with frequent package dropouts, the hybrid adaptive strategy achieves the coordination among communication resource utilization, string stability margin, distance accuracy, and traffic efficiency.

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8.

Adaptive Fitting Capacity Prediction Method for Lithium-Ion Batteries

Xiao Chu, Fangyu Xue, Tao Liu, Junya Shao, Junfu Li

Automotive Innovation 2022, 5 (4): 359-375. DOI: 10.1007/s42154-022-00201-4

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Lithium-ion batteries have become the mainstream power source for electric vehicles because of their excellent performance. However, lithium-ion batteries still experience aging and capacity attenuation during usage. It is therefore critical to accurately predict battery remaining capacity for increasing battery safety and prolonging battery life. This paper first adopts the metabolism grey algorithm and a simplified electrochemical model to predict battery capacity under different operating conditions. To improve the prediction performance where the capacity changes nonlinearly, a decoupling analysis of battery capacity loss is then conducted based on the simplified electrochemical model. Finally, an adaptive fitting method is developed for capacity prediction, aiming at improving the prediction accuracy at the inflection point of battery capacity diving. The prediction results indicate that the developed adaptive fitting method can achieve high prediction accuracy under battery capacity attenuation at different discharge stages with errors lower than 2.2%. And the battery capacity decay shows linear variation, and the proposed method effectively forecast the inflection point of battery capacity diving.

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9.

Preface for Feature Topic on Advanced Battery Management for Electric Vehicles

Xiaosong Hu

Automotive Innovation 2022, 5 (2): 105-106. DOI: 10.1007/s42154-022-00182-4

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With the growing demand for energy resources and rising environmental risks, the deployment of electric vehicles has been recognized as effective countermeasures to the global energy crisis and climate change. Lithium-ion batteries, thanks to their high efficiency, high energy/power density, and long lifespan, are widely used as critical energy storage devices for electric vehicles. Meanwhile, traction batteries play a deciduous role in the reliability, availability, maintainability, and safety of electric vehicles. Therefore, they should be meticulously designed and managed.

The development of advanced battery management systems has become the forefront of research worldwide. Upgraded modeling, estimation, control, and optimization of battery systems are researched in order to improve the battery performance while guaranteeing its safety. Interdisciplinary knowledge, including electrical engineering, control theory, electrochemistry, AI, and machine learning, needs to be integrated in an appropriate way to seek high-performance battery management.

Four articles have been collected in this feature topic with salient contributions to the field of battery management. The feature topic highlights the most recent advances in battery modeling, health and safety management. The four articles, as listed below, cover the topics of battery fault prognosis and diagnosis, data-driven modeling of the electrode, state of health estimation, and non-invasive characteristic analysis.

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10.

Internal Short Circuit Detection for Parallel-Connected Battery Cells Using Convolutional Neural Network

Niankai Yang, Ziyou Song, Mohammad Reza Amini & Heath Hofmann

Automotive Innovation 2022, 5 (2): 107-120. DOI: 10.1007/s42154-022-00180-6

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Reliable and timely detection of an internal short circuit (ISC) in lithium-ion batteries is important to ensure safe and efficient operation. This paper investigates ISC detection of parallel-connected battery cells by considering cell non-uniformity and sensor limitation (i.e., no independent current sensors for individual cells in a parallel string). To characterize ISC-related signatures in battery string responses, an electro-thermal model of parallel-connected battery cells is first established that explicitly captures ISC. By analyzing the data generated from the electro-thermal model, the distribution of surface temperature among individual cells within the battery string is identified as an indicator for ISC detection under the constraints of sensor limitations. A convolutional neural network (CNN) is then designed to estimate the ISC resistance by using the cell surface temperature and the total capacity of the string as inputs. Based on the estimated ISC resistance from CNN, the strings are classified as faulty or non-faulty to guide the examination or replacement of the battery. The algorithm is evaluated in the presence of signal noises in terms of accuracy, false alarm rate, and missed detection rate, verifying the effectiveness and robustness of the proposed approach.

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11.

Heating Lithium-Ion Batteries at Low Temperatures for Onboard Applications: Recent Progress, Challenges and Prospects

Cheng Lin, Weifeng Kong, Yu Tian, Wenwei Wang & Mingjie Zhao

Automotive Innovation 2022, 5 (1): 3-17. DOI: 10.1007/s42154-021-00166-w

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Lithium-ion batteries (LIBs) are commonly used in electric vehicles (EVs) due to their good performance, long lifecycle,
and environmentally friendly merits. Heating LIBs at low temperatures before operation is vitally important to protect the
battery from serious capacity degradation and safety hazards. This paper reviews recent progress on heating methods that
can be used onboard. The existing methods are divided into two categories, namely external heating methods and internal
heating methods, mechanisms, advantages and limitations of each method are systematically reviewed. Then, the rates of
temperature rise, energy consumptions, and maximum temperature gradient of diferent methods are quantitatively summarized to compare the heating performances of each method. In addition, features related to the onboard application of each method are qualitatively compared, which is essential for the rapid cold start of EVs in frigid weather. Finally, prospects of external and internal heating methods are given. This paper aims to provide researchers and engineers with guidelines about how to select a method based on their requirements and application environments.

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12.

Collaborative Control of Novel Uninterrupted Propulsion System for All-Climate Electric Vehicles

Cheng Lin, Xiao Yu, Mingjie Zhao, Jiang Yi & Ruhui Zhang

Automotive Innovation 2022, 5 (1): 18-28. DOI: 10.1007/s42154-021-00170-0

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Over the past decade, the electric vehicle industry of China has developed rapidly, reaching one of the highest technological levels in the world. Nevertheless, most electric buses currently serve urban areas, being unsuitable for all-climate operations. In response to the objective of massively adopting electric vehicles for transportation during all the events of the 2022 Beijing Winter Olympics, a dual-motor coaxial propulsion system for all-climate electric vehicles is proposed. The system aims to meet operating requirements such as high speed and adaptability to mountainous roads under severely cold environments. The system provides three operating modes, whose characteristics are analyzed under different conditions. In addition, dual-motor collaborative control strategy with collaborative gearshift and collaborative power distribution is proposed to eliminate power interruption during gearshift process and achieve intelligent power distribution, thus improving the gearshift quality and reducing energy consumption. Finally, gear position calibration for all-climate operation and proper gearshift is introduced. Experimental results demonstrate the advantages of the proposed dual-motor coaxial propulsion system regarding gearshift compared with the conventional single-motor automatic transmission.

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13.

Review of DC-DC Converter Topologies Based on Impedance Network with Wide Input Voltage Range and High Gain for Fuel Cell Vehicles

Xiaogang Wu, Jiulong Wang, Yun Zhang, Jiuyu Du, Zhengxin Liu & Yu Chen

Automotive Innovation 2021, 4 (4): 351-372. DOI: 10.1007/s42154-021-00163-z

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The development of fuel cell vehicles (FCVs) has a major impact on improving air quality and reducing other fossil-fuel-related problems. DC-DC boost converters with wide input voltage ranges and high gains are essential to fuel cells and DC buses in the powertrains of FCVs, helping to improve the low voltage of fuel cells and “soft” output characteristics. To build DC-DC converters with the desired performance, their topologies have been widely investigated and optimized. Aiming to obtain the optimal design of wide input range and high-gain DC-DC boost converter topologies for FCVs, a review of the research status of DC-DC boost converters based on an impedance network is presented. Additionally, an evaluation system for DC-DC topologies for FCVs is constructed, providing a reference for designing wide input range and high-gain boost converters. The evaluation system uses eight indexes to comprehensively evaluate the performance of DC-DC boost converters for FCVs. On this basis, issues about DC-DC converters for FCVs are discussed, and future research directions are proposed. The main future research directions of DC-DC converter for FCVs include utilizing a DC-DC converter to realize online monitoring of the water content in FCs and designing buck-boost DC-DC converters suitable for high-power commercial FCVs.

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14.

Simulator Coupled with Distributed Co-Simulation Protocol for Automated Driving Tests

Max-Arno Meyer, Lina Sauter, Christian Granrath, Hassen Hadj-Amor & Jakob Andert

Automotive Innovation 2021, 4 (4): 373-389. DOI: 10.1007/s42154-021-00161-1

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To meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.

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15.

Preface for Feature Topic on Intelligent Safety for CAVs

Jun Li & Hong Wang

Automotive Innovation 2021, 4 (3): 239-240. DOI: 10.1007/s42154-021-00158-w

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Connected and automated driving confronts critical complex traffic scenarios and safety, which attracts increasing attention from academia and industry. To enhance the intelligent safety for connected and automated vehicles (CAVs), including functional safety, safety of the intended functionality (SOTIF), and cybersecurity, efforts are required to seek solutions from fundamental theory, guarantee framework and general/systematic point of view. This feature topic aims to provide a platform for academia, industry, and policymakers, on which they could present the latest research and engineering experience in developing and applying novel technologies. The topics cover SOTIF, cybersecurity, artificial intelligence for CAV safety, risk assessment-based vehicle path planning and decision-making under uncertain environments.

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16.

Uncertainty Evaluation of Object Detection Algorithms for Autonomous Vehicles

Liang Peng, Hong Wang & Jun Li

Automotive Innovation 2021, 4 (3): 241-252. DOI: 10.1007/s42154-021-00154-0

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The safety of the intended functionality (SOTIF) has become one of the hottest topics in the field of autonomous driving. However, no testing and evaluating system for SOTIF performance has been proposed yet. Therefore, this paper proposes a framework based on the advanced You Only Look Once (YOLO) algorithm and the mean Average Precision (mAP) method to evaluate the object detection performance of the camera under SOTIF-related scenarios. First, a dataset is established, which contains road images with extreme weather and adverse lighting conditions. Second, the Monte Carlo dropout (MCD) method is used to analyze the uncertainty of the algorithm and draw the uncertainty region of the predicted bounding box. Then, the confidence of the algorithm is calibrated based on uncertainty results so that the average confidence after calibration can better reflect the real accuracy. The uncertainty results and the calibrated confidence are proposed to be used for online risk identification. Finally, the confusion matrix is extended according to the several possible mistakes that the object detection algorithm may make, and then the mAP is calculated as an index for offline evaluation and comparison. This paper offers suggestions to apply the MCD method to complex object detection algorithms and to find the relationship between the uncertainty and the confidence of the algorithm. The experimental results verified by specific SOTIF scenarios proof the feasibility and effectiveness of the proposed uncertainty acquisition approach for object detection algorithm, which provides potential practical implementation chance to address perceptual related SOTIF risk for autonomous vehicles.

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17.

Preface for Special Section on Fuel Cell Technology

Cunman Zhang

Automotive Innovation 2021, 4 (2): 117-118. DOI: 10.1007/s42154-021-00150-4

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In this special section, we have gathered 5 papers with significant contributions in the field of fuel cell, which reflects the latest advances in developing and understanding the design and optimization of key materials and components of fuel cells. The papers, as listed below, cover the topics of carbon support evaluation, Pt-free cathode electrocatalyst, cathode catalyst layer design, local behaviours characterization of fuel cell and heat exchanger numerical analysis.

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18.

Modifying Carbon Supports of Catalyst for the Oxygen Reduction Reaction in Vehicle PEMFCs

Qiong Xue, Daijun Yang, Lei Jiang, Bing Li & Pingwen Ming

Automotive Innovation 2021, 4 (2): 119-130. DOI: 10.1007/s42154-021-00149-x

摘要（24）

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For current carbon-supported Pt catalysts in vehicle proton exchange membrane fuel cells (PEMFCs), the insufficient stability and durability of carbon supports are severe limitations under operating conditions. This paper adopts the accelerated stress test (AST) method to study the carbon corrosion of catalysts, which is significant to efficiently select the catalysts supports in fuel cells. Graphitized carbon blacks with various surface properties are heated under different conditions, followed by evaluation of their antioxidation capacity with the AST. It is shown that optimally graphitized carbon blacks demonstrate superior stability, retaining a constant quinone/hydroquinone (QH) transition peak potential for over 70,000 AST cycles. A Pt catalyst supported on the selected graphitized carbon exhibits excellent durability at both the rotating disk electrode (RDE) and membrane electrode assembly (MEA) levels. The final specific mass activity (MA) of the optimum catalyst is 47.87 mA/mgPt, which is 2.06 times that of commercial Pt/C (23.31 mA/mgPt) in the RDE tests. The final maximum power density of the optimum catalyst is 525.68 mW/cm2, which is 305.52 mW/cm2 higher than that of commercial Pt/C after undergoing the AST during the MEA measurements. These results prove that the rational surface features of carbon supports play a vital role in improving the overall fuel cell performance by realizing uniform dispersion of Pt nanoparticles, resisting corrosion, and reinforcing metal–support interactions.

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19.

Proton Exchange Membrane (PEM) Fuel Cells with Platinum Group Metal (PGM)-Free Cathode

Lei Du, Gaixia Zhang & Shuhui Sun

Automotive Innovation 2021, 4 (2): 131-143. DOI: 10.1007/s42154-021-00146-0

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Proton exchange membrane (PEM) fuel cells have gained increasing interest from academia and industry, due to its remarkable advantages including high efficiency, high energy density, high power density, and fast refueling, also because of the urgent demand for clean and renewable energy. One of the biggest challenges for PEM fuel cell technology is the high cost, attributed to the use of precious platinum group metals (PGM), e.g., Pt, particularly at cathodes where sluggish oxygen reduction reaction takes place. Two primary ways have been paved to address this cost challenge: one named low-loading PGM-based catalysts and another one is non-precious metal-based or PGM-free catalysts. Particularly for the PGM-free catalysts, tremendous efforts have been made to improve the performance and durability—milestones have been achieved in the corresponding PEM fuel cells. Even though the current status is still far from meeting the expectations. More efforts are thus required to further research and develop the desired PGM-free catalysts for cathodes in PEM fuel cells. Herein, this paper discusses the most recent progress of PGM-free catalysts and their applications in the practical membrane electrolyte assembly and PEM fuel cells. The most promising directions for future research and development are pointed out in terms of enhancing the intrinsic activity, reducing the degradation, as well as the study at the level of fuel cell stacks.

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20.

Review and Development of Electric Motor Systems and Electric Powertrains for New Energy Vehicles

William Cai, Xiaogang Wu, Minghao Zhou, Yafei Liang & Yujin Wang

Automotive Innovation 2021, 4 (1): 3-22. DOI: 10.1007/s42154-021-00139-z

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This paper presents a review on the recent research and technical progress of electric motor systems and electric powertrains for new energy vehicles. Through the analysis and comparison of direct current motor, induction motor, and synchronous motor, it is found that permanent magnet synchronous motor has better overall performance; by comparison with converters with Si-based IGBTs, it is found converters with SiC MOSFETs show significantly higher efficiency and increase driving mileage per charge. In addition, the pros and cons of different control strategies and algorithms are demonstrated. Next, by comparing series, parallel, and power split hybrid powertrains, the series–parallel compound hybrid powertrains are found to provide better fuel economy. Different electric powertrains, hybrid powertrains, and range-extended electric systems are also detailed, and their advantages and disadvantages are described. Finally, the technology roadmap over the next 15 years is proposed regarding traction motor, power electronic converter and electric powertrain as well as the key materials and components at each time frame.

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21.

Study of Series-Parallel and Power-Split DHT for Hybrid Powertrains

Haijun Chen, Lin Li & Ferit Küçükay

Automotive Innovation 2021, 4 (1): 23-33. DOI: 10.1007/s42154-020-00126-w

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Dedicated hybrid transmission (DHT) is the developing trend of hybrid transmissions. This paper studies different types of DHTs regarding the structure, function, and performance. Firstly, the structure and function of different well-known DHTs in the market are discussed and analyzed. Through the analysis, the reasonability and necessity of the different modes and the electric motor power requirements that lie behind different DHTs are derived. Secondly, the dynamics of different DHTs are further compared with the driving areas in different modes under different driving conditions. Then, the basic or minimum dynamic requirements are defined and taken into consideration before the economic comparison. To ensure the effectiveness of the comparison, the optimization of the configurations for each kind of DHT is carried out with the modular simulation model. The economic comparison is conducted under the premise of excluding the influences of the configurations in the results. Finally, the sensitivity and influence of different engine characteristics for different DHTs are studied to find out the sensibilities of the two kinds of DHTs with engine technology. Through these studies, the essential differences and features of different DHTs can be derived to help better understand the decision in choosing the technical route for the original equipment manufacturers.

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22.

Thermal Management of Electrified Propulsion System for Low-Carbon Vehicles

Bo Li, Huang Kuo, Xuehui Wang, Yiyi Chen, Yangang Wang, David Gerada, Sean Worall, Ian Stone & Yuying Yan

Automotive Innovation 2020, 3 (4): 299-316. DOI: 10.1007/s42154-020-00124-y

摘要（59）

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An overview of current thermal challenges in transport electrification is introduced in order to underpin the research developments and trends of recent thermal management techniques. Currently, explorations of intelligent thermal management and control strategies prevail among car manufacturers in the context of climate change and global warming impacts. Therefore, major cutting-edge systematic approaches in electrified powertrain are summarized in the first place. In particular, the important role of heating, ventilation and air-condition system (HVAC) is emphasised. The trends in developing efficient HVAC system for future electrified powertrain are analysed. Then electric machine efficiency is under spotlight which could be improved by introducing new thermal management techniques and strengthening the efforts of driveline integrations. The demanded integration efforts are expected to provide better value per volume, or more power output/torque per unit with smaller form factor. Driven by demands, major thermal issues of high-power density machines are raised including the comprehensive understanding of thermal path, and multiphysics challenges are addressed whilst embedding power electronic semiconductors, non-isotropic electromagnetic materials and thermal insulation materials. Last but not least, the present review has listed several typical cooling techniques such as liquid cooling jacket, impingement/spray cooling and immersion cooling that could be applied to facilitate the development of integrated electric machine, and a mechanic-electric-thermal holistic approach is suggested at early design phase. Conclusively, a brief summary of the emerging new cooling techniques is presented and the keys to a successful integration are concluded.

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23.

Thermal Analyses of Power Electronics Integrated with Vapour Chamber Cooling

Yiyi Chen, Yuying Yan & Bo Li

Automotive Innovation 2020, 3 (4): 328-335. DOI: 10.1007/s42154-020-00123-z

摘要（40）

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Insulated gate bipolar transistor (IGBT) power module is used for power switching transistor devices in the power supply and motor control circuits in both hybrid electric vehicles and electric vehicles. The target of heat flux of IGBT is continuously increasing due to the demand for power rating improvements and miniaturisation. Without suitable efficient cooling technologies, excessively high temperature and uneven temperature distribution can cause high thermal stress, eventually leading to severe module failures. Therefore, highly efficient cooling solutions are highly required. Vapour chamber with phase change can provide quick heat transfer and low temperature gradient. This study proposes a new IGBT structure integrated with vapour chamber. The tests and simulation results indicate that the thermal and thermo-mechanical performances of IGBT integrated with vapour chamber are better than those of the IGBT with copper baseplate module. The thermal resistance between the junction and heat sink is reduced from 0.25 to 0.14 °C/W, and the temperature uniformity is greatly improved due to the phase change in the vapour chamber. The simulation also investigates the thermal stress distribution, deformation and thermal fatigue lifespan of IGBT power electronics module. A reduction of 21.8% in thermal stress and an increase of 9% in lifespan of Sn–3.5Ag solder are achieved.

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24.

Special Issue on Automotive Lightweight

A. Erman Tekkaya & Junying Min

Automotive Innovation 2020, 3 (3): 193-194. DOI: 10.1007/s42154-020-00117-x

摘要（88）

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Lightweight is one of the core technologies to realize energy saving, to improve the safety and driving performance of vehicles, and to provide added passenger comfort as well. It is of special significance for increasing cruising range of electric or hybrid-powered vehicles. Beyond these, lightweight components use less mass and hence reduce the primary energy requirement imbedded in the component. Therefore, lightweight has always been a central topic and an important direction in the automotive field whether in the past or in the future.

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25.

Lightweight in Automotive Components by Forming Technology

Stephan Rosenthal, Fabian Maaß, Mike Kamaliev, Marlon Hahn, Soeren Gies & A. Erman Tekkaya

Automotive Innovation 2020, 3 (3): 195-209. DOI: 10.1007/s42154-020-00103-3

摘要（73）

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Lightweight design is one of the current key drivers to reduce the energy consumption of vehicles. Design methodologies for lightweight components, strategies utilizing materials with favorable specific properties and hybrid materials are used to increase the performance of parts for automotive applications. In this paper, various forming processes to produce light parts are described. Material lightweight design is discussed, covering the manufacturing processes to produce hybrid components like fiber–metal, polymer–metal and metal–metal composites, which can be used in subsequent deep drawing or combined forming processes. Approaches to increasing the specific strength and stiffness with thermomechanical forming processes as well as the in situ control of the microstructure of such components are presented. Structure lightweight design discusses possibilities to plastically form high-strength or high-performance materials like magnesium or titanium in sheet, profile and tube forming operations. To join those materials and/or dissimilar materials, new joining by forming technologies are shown. To economically produce lightweight parts with gears or functional elements, incremental sheet-bulk metal forming is presented. As an important part property, the damage evolution during the forming operations will be discussed to enable even lighter parts through a more reliable design. New methods for predicting and tailoring the mechanical properties like strength and residual stresses will be shown. The possibilities of system lightweight design with forming technologies are presented. A combination of additive manufacturing and forming to produce highly complex parts with integrated functions will be shown. The integration of functions by a hot extrusion process for the manufacturing of shape memory alloys is presented. An in-depth understanding of the newly developed processes, methodologies and effects allows for a more accurate dimensioning of components. This facilitates a reduction in the total mass and an increasing performance of vehicle components.

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26.

Experimental Study on Hydrogen Leakage and Emission of Fuel Cell Vehicles in Confined Spaces

Dong Hao, Xiaobing Wang, Yanyi Zhang, Renguang Wang, Guang Chen & Jun Li

Automotive Innovation 2020, 3 (2): 111-122. DOI: 10.1007/s42154-020-00096-z

摘要（69）

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Hydrogen safety is one of the most important safety indicators in fuel cell vehicles (FCVs) (unlike in other types of alternative energy vehicles). This indicator in FCVs is directly related to the user’s personal safety in daily vehicle usage. This paper analyzes the safety standards of FCVs in confned spaces. A sealed test chamber and an appropriate test method are developed to evaluate vehicle safety based on specifc test requirements. Two FCVs are subjected to static hydrogen leakage and hydrogen emission testing performed in a confned space. The results reveal that the hydrogen concentration in the vicinity of the vehicles approximates 0.0004% which is much lower than 1% while parked for 8 h during the hydrogen leakage test. In the hydrogen emission test under operating conditions, the concentration of the hydrogen gas emitted from the vehicles exceeds 2300 ppm in the vicinity, which requires careful consideration. Based on experiment and analysis, recommendations for the hydrogen safety standards of FCVs in confned spaces are proposed.

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27.

Stability Design for the Homogeneous Platoon with Communication Time Delay

Fangwu Ma, Jiawei Wang, Yu Yang, Liang Wu, Sheng Zhu, Sukru Yaren Gelbal, Bilin Aksun-Guvenc & Levent Guvenc

Automotive Innovation 2020, 3 (2): 101-110. DOI: 10.1007/s42154-020-00102-4

摘要（68）

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A hierarchical control framework is applied for the distributed cooperative vehicular platoon using vehicular ad-hoc networks. The parameter-space-approach-based cooperative adaptive cruise control (CACC) controller is proposed to guarantee the D-stability and the string stability considering the influence of the communication time delay and time lag of vehicular dynamic performance. This CACC controller combines the feedforward loop of the acceleration of the preceding vehicle with the feedback loop of the following errors, in which the gain of the feedforward loop is designed to decrease matching errors and the gains of the feedback loop are selected from the feasible region in the parameter space. To verify the effectiveness of the CACC controller, a six-vehicle platoon with a simplified vehicular dynamic is simulated under speed-up and stop scenarios. The simulation results demonstrate that the disturbance is attenuated along with the platoon and the following errors are convergent with well-designed convergent performance. A CarSim/Simulink co-simulation is designed to further verify the effectiveness of the hierarchical control framework and the rationality of the CACC controller in the real vehicular platoon application. The simulation results under the highway fuel economy test drive cycle show that the CACC controller improves the drive comfort and significantly decreases the following errors.

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28.

Special Issue on HMI and Autonomous Driving

Fang Chen

Automotive Innovation 2020, 3 (1): 1-2. DOI: 10.1007/s42154-020-00094-1

摘要（92）

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Human-machine interaction (HMI) is about the interaction design inside the cockpit of vehicle. It takes the human-centered design approach related to systems that help driver or passengers’ communication with vehicles. Ensuring safer driving and more effective communication between the human and the vehicle is the central focus. Its design challenges have changed a lot due to the increasing level of autonomous driving. What kind of interaction will be the mainstream? How would a driver’s personality influence the driver’s attitude toward active safety and trust of the autonomous driving? How should HMI be designed for the handover scenarios from Level 3 to Level 5 autonomous driving? What HMI solutions make the driving safer and improve user experience?

This special issue includes eight papers. The first five papers seek to address the above questions by assessing the current approaches and technologies, as well as to outline the major challenges and future perspectives related to HMI technology applied in intelligent vehicles. The other three papers are related to autonomous driving.

We hope this special issue could motivate research in the vehicle HMI design and promote the building of quality criteria for automotive user interfaces and autonomous driving systems in the automotive industry.

We would first like to gratefully acknowledge and sincerely thank all the reviewers for their timely and insightful valuable comments and criticism of the manuscripts that greatly improved the quality of the final versions. Of course, thanks are due to the authors, who provided excellent papers and timely extended revisions. Finally, we are grateful to the editors of Automotive Innovation for their trust in us, their efforts, patience, and painstaking editorial work during the production of this special issue.

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29.

Personality Openness Predicts Driver Trust in Automated Driving

Wenmin Li, Nailang Yao, Yanwei Shi, Weiran Nie, Yuhai Zhang, Xiangrong Li, Jiawen Liang, Fang Chen & Zaifeng Gao

Automotive Innovation 2020, 3 (1): 3-13. DOI: 10.1007/s42154-019-00086-w

摘要（99）

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Maintaining an appropriate level of trust in automated driving (AD) is critical to safe driving. However, few studies have explored factors affecting trust in AD in general, and no study, as far as is known, has directly investigated whether driver personality influences driver trust in an AD system. The current study investigates the relation between driver personality and driver trust in AD, focusing on Level 2 AD. Participants were required to perform a period of AD in a driving simulator, during which their gaze and driving behavior were recorded, as well as their subjective trust scores after driving. In three distinct measures, a significant correlation between Openness and driver trust in the AD system is found: participants with higher Openness traits tend to have less trust in the AD system. No significant correlations between driver trust in AD and other personality traits are found. The findings suggest that driver personality has an impact on driver trust in AD. Theoretical and practical implications of this finding are discussed.

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30.

Comprehensive Analysis and Optimization of Dynamic Vibration-Absorbing Structures for Electric Vehicles Driven by In-Wheel Motors

Yechen Qin, Zhenfeng Wang, Kang Yuan, Yubiao Zhang

Automotive Innovation 2019, 2 (4): 254-262. DOI: 10.1007/s42154-019-00079-9

摘要（77）

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Distributed-drive electric vehicles (EVs) replace internal combustion engine with multiple motors, and the novel configuration results in new dynamic-related issues. This paper studies the coupling effects between the parameters and responses of dynamic vibration-absorbing structures (DVAS) for EVs driven by in-wheel motors (IWM). Firstly, a DVAS-based quarter suspension model is developed for distributed-drive EVs, from which nine parameters and five responses are selected for the coupling effect analysis. A two-stage global sensitivity analysis is then utilized to investigate the effect of each parameter on the responses. The control of the system is then converted into a multiobjective optimization problem with the defined system parameters being the optimization variables, and three dynamic limitations regarding both motor and suspension subsystems are taken as the constraints. A particle swarm optimization approach is then used to either improve ride comfort or mitigate IWM vibration, and two optimized parameter sets for these two objects are provided at last. Simulation results provide in-depth conclusions for the coupling effects between parameters and responses, as well as a guideline on how to design system parameters for contradictory objectives. It can be concluded that either passenger comfort or motor lifespan can be reduced up to 36% and 15% by properly changing the IWM suspension system parameters.

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31.

Driving Space for Autonomous Vehicles

Diange Yang, Xinyu Jiao, Kun Jiang, Zhong Cao

Automotive Innovation 2019, 2 (4): 241-253. DOI: 10.1007/s42154-019-00081-1

摘要（82）

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Driving space for autonomous vehicles (AVs) is a simplified representation of real driving environments that helps facilitate driving decision processes. Existing literatures present numerous methods for constructing driving spaces, which is a fundamental step in AV development. This study reviews the existing researches to gain a more systematic understanding of driving space and focuses on two questions: how to reconstruct the driving environment, and how to make driving decisions within the constructed driving space. Furthermore, the advantages and disadvantages of different types of driving space are analyzed. The study provides further understanding of the relationship between perception and decision-making and gives insight into direction of future research on driving space of AVs.

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32. Cooperative Lane-Change Maneuver for Multiple Automated Vehicles on a Highway

Yugong Luo, Gang Yang, Mingchang Xu, Zhaobo Qin, Keqiang Li

Automotive Innovation 2019, 2 (3): 157-168. DOI: 10.1007/s42154-019-00073-1

摘要（32）

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With the development of vehicle-to-vehicle (V2V) communication, it is possible to share information among multiple vehicles. However, the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information. Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency. Therefore, a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed. In these scenarios, same-direction and intersectant-direction cooperative lane changes were defined. The vehicle that made the cooperative decision obtained the information of surrounding vehicles that were used to cooperatively plan the trajectories, which was called cooperative trajectory planning. The cooperative safety spacing model was proposed to guarantee and improve the safety of all vehicles, and it essentially developed constraints for the trajectory-planning task. Trajectory planning was treated as an optimization problem with the objective of maximizing safety, comfort, and lane-change efficiency under the constraints of vehicle dynamics and the aforementioned safety spacing model. Trajectory tracking based on a model predictive control method was designed to minimize tracking errors and control increments. Finally, to verify the validity of the proposed maneuver, an integrated simulation platform combining MATLAB/Simulink with CarSim was established. Moreover, a hardware-in-the-loop test bench was performed for further verification. The results indicated that the proposed multi-vehicle cooperative automated lane-change maneuver can achieve lane changes of multiple vehicles and increase lane-change efficiency while guaranteeing safety and comfort.

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33. Modeling and Simulating a Battery for an Electric Vehicle Based on Modelica

Dongchen Qin, Jianjie Li, Tingting Wang, Dongming Zhang

Automotive Innovation 2019, 2 (3): 169-177. DOI: 10.1007/s42154-019-00066-0

摘要（16）

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Battery is the key technology to the development of electric vehicles, and most battery models are based on the electric vehicle simulation. In order to accurately study the performance of LiFePO4 batteries, an improved equivalent circuit model was established by analyzing the dynamic characteristics and contrasting different-order models of the battery. Compared to the traditional model, the impact of hysteresis voltage was considered, and the third-order resistance–capacitance (RC) network was introduced to better simulate internal battery polarization. The electromotive force, resistance, capacitance and other parameters were calibrated through battery charge and discharge experiments. This model was built by using Modelica, a modeling language for object-oriented multi-domain physical systems. MWorks was used to implement the cycle conditions and vehicle simulation. The results show that the third-order RC battery model with hysteretic voltage well reflects the dynamics of a LiFePO4 battery. The difference between the simulated and measured voltages is small, with a maximum error of 1.78%, average error of 0.23%. The validity and feasibility of the model are verified. It can be used in unified modeling and simulation of subsequent multi-domain systems of electric vehicles.

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34. Numerical Implementation of High-Order Vold–Kalman Filter Using Python Arbitrary-Precision Arithmetic Library

Linhe Ge, Fangwu Ma, Jinzhu Shi, Hongbin Yin, Ying Zhao

Automotive Innovation 2019, 2 (3): 178-189. DOI: 10.1007/s42154-019-00065-1

摘要（77）

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The Vold–Kalman (VK) order tracking filter plays a vital role in the order analysis of noise in various fields. However, owing to the limited accuracy of double-precision floating-point data type, the order of the filter cannot be too high. This problem of accuracy makes it impossible for the filter to use a smaller bandwidth, meaning that the extracted order signal has greater noise. In this paper, the Python mpmath arbitrary-precision floating-point arithmetic library is used to implement a high-order VK filter. Based on this library, a filter with arbitrary bandwidth and arbitrary difference order can be implemented whenever necessary. Using the proposed algorithm, a narrower transition band and a flatter passband can be obtained, a good filtering effect can still be obtained when the sampling rate of the speed signal is far lower than that of the measured signal, and it is possible to extract narrowband signals from signals with large bandwidth. Test cases adopted in this paper show that the proposed algorithm has better filtering effect, better frequency selectivity, and stronger anti-interference ability compared with double-precision data type algorithm.

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35. Characterization of Automotive Brake Discs with Laser-Machined Surfaces

Shuwen Wang, Wang Guo, Kang Zeng, Xuegang Zhang

Automotive Innovation 2019, 2 (3): 190-200. DOI: 10.1007/s42154-019-00068-y

摘要（48）

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In the automotive and transport industry, braking noise and vibrations are persisting issues and difficult to control. Automotive engineers and researchers are putting considerable effort into overcoming these problems, and significant breakthroughs have been made in this area. In this study, M-shaped grooves were bionically designed and manufactured on the frictional surfaces of four automotive brake discs using a laser machine. Various tests were conducted to characterize the physical and mechanical performance of the modified discs along with their noise and vibration responses. The experimental results demonstrate that discs with laser-machined grooved surfaces have better surface hardness and residual stress reduction than discs with un-grooved surfaces. Significant improvement in the braking performance was observed in terms of disc thickness variation, friction and wear, noise, and vibration reduction. It is concluded that the reduction in braking noise and vibrations is mainly caused by the reduction in the coefficient of friction and wear, increase in damping ratio, and improvement of disc thickness variation of the brake disc by laser surface grooving.

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36. Innovative Electric Vehicle Body Design Based on Insurance Institute for Highway Safety Side Impact Conditions

Xinchun Liu, Maoyan Liang, Qiang Luo

Automotive Innovation 2019, 2 (3): 201-211. DOI: 10.1007/s42154-019-00070-4

摘要（55）

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A version of an electric vehicle was developed and designed for the US market on the basis of the required domestic body structure. When compared with the original car, the new car body design leads to two major technical difficulties. First, the installation of high-voltage components such as the battery pack and other new energy sources increases the vehicle weight and occupies a great deal of its structural space; this limits the impact paths and the use of traditional structural designs, which greatly increases the design difficulty. Second, the USA, as an advanced automobile-using country, has well-developed laws and regulations for collision standards, vehicle operating conditions and evaluation standards. Using a combination of butterfly diagram analysis, bending moment management, section forces and other computer-aided simulation and analysis techniques, this paper presents a body structure design that can achieve a “GOOD” evaluation under the US Insurance Institute for Highway Safety (IIHS) side impact body structure conditions by optimizing the force transfer path, the B-pillar deformation mode and the threshold support structure. The threshold support structure supports realization of the “GOOD” rating for IIHS side impact and helps the body to meet the crash requirements of the Federal Motor Vehicle Safety Standard FMVSS214 and the US New Car Assessment Program (NCAP) requirements for side impact at 32 km/h and 75° angular pole impact.

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37. Hardware Design and Test of a Gear-Shifting Control System of a Multi-gear Transmission for Electric Vehicles

Feng Tian, Liqi Sui, Yuanfan Zeng, Bo Li, Xingyue Zhou, Lijun Wang, Hongxu Chen

Automotive Innovation 2019, 2 (3): 212-222. DOI: 10.1007/s42154-019-00072-2

摘要（64）

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The performance of electric vehicles is affected by the shift quality of multi-gear transmission. The realization of dual-target tracking control requires the transmission control unit (TCU) to accurately measure and process the input signals of the gear-shifting control system and precisely control the drive motor torque and the position of shift motors. An electric-vehicle-dedicated TCU was designed to meet the above design requirements. Its function modules included a single-chip control circuit, shift position signal sampling circuit, signal conditioning circuit of the rotational speed and angle, controller area network communication circuit, and shift motor drive circuit. A hardware-in-the-loop simulation test system showed that the TCU design scheme met measurement accuracy requirements and coordinated the actions of the shift actuator and motor control unit to achieve fast and smooth shifting before the road test. The power interruption time of the shifting process was within 350 ms. The reliability of the TCU design was further verified in a 150,000-km vehicle road test.

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38. Multiphysics Field Co-simulation Research Based on Electric Drive System for a Specific Type of Car

Chuanfu Wang, Yubo Lian, Heping Ling, Hua Pan, Yuxin Zhang

Automotive Innovation 2019, 2 (3): 223-230. DOI: 10.1007/s42154-019-00067-z

摘要（62）

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Electric drive systems for new energy cars are complex systems that should have multivariate, strong coupling, and nonlinear characteristics and should also involve the multiphysics field. The singular simulation software used at present in the modeling of electric drive systems cannot simulate the influences of all the physics fields on the operating system. The co-simulation model used in this paper was based on a specific type of car. The motor control algorithm model was built in MATLAB/Simulink, the electromagnetic finite element model of the motor was built in ANSYS EM-Maxwell, and the motor controller hardware circuit was built in ANSYS EM-Simplorer. To make real-time connections among these software platforms, a multi-software co-simulation platform was built, and the co-simulation platform’s simulation results were input into STAR CCM+ software to enable finite element modeling of the motor and running of thermal analysis. When compared with the electric drive system model built using single Simulink software, the simulation results from this co-simulation platform were more realistic and were shown to be closer to reality when the dynamic characteristics of the electric drive system’s power semiconductor switching devices and the motor’s electromagnetic characteristics were considered. Finally, by benchmarking the multiphysics field co-simulation platform simulation results using dyno bench test results, the validity of the co-simulation platform was verified and the development of the multiphysics field co-simulation of the basic electric drive system was complete.

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39. Systematic Synthesis of Dedicated Hybrid Transmission

Lin Li, Haijun Chen, Ferit Küçükay

Automotive Innovation 2019, 2 (3): 231-239. DOI: 10.1007/s42154-019-00071-3

摘要（55）

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The great diversity of dedicated hybrid transmissions (DHTs) requires a method to identify solutions among all potential concepts involved in each structure. Therefore, a DHT synthesis tool is developed on the basis of general transmission synthesis. In the first synthesis step, transmission structures are generated with only conventional functions such as driving with only the internal combustion engine. Electric machines are then installed in the transmissions to achieve further hybrid functions, including boosting, eCVT and electric driving modes. The number of generated transmission concepts increases exponentially with each synthesis step. Various evaluations are carried out successively to identify the most suitable DHT concepts among the many possible solutions. The generated DHT concepts are evaluated in terms of structural feasibility, driving modes, drivability and load factors on transmission components. An example of DHT synthesis involving planetary gear sets is explained in detail. The best five DHT structures are identified out of more than 120 billion solutions.

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40. A Review of Engine Fuel Injection Studies Using Synchrotron Radiation X-ray Imaging

Zhijun Wu, Wenbo Zhao, Zhilong Li, Jun Deng, Zongjie Hu, Liguang Li

Automotive Innovation 2019, 2 (2): 79-92. DOI: 10.1007/s42154-019-00056-2

摘要（71）

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Fuel spray characteristics directly determine the formation pattern and quality of the fuel/air mixture in an engine, and thus affect the combustion process. For this reason, the improvement and optimization of fuel injection systems is crucial to the development of engine technologies. The fuel jet breakup and atomization process is a complex liquid–gas two-phase turbulent flow system that has not yet been fully elucidated. Owing to the limitations of standard optical measurement techniques, the spray breakup mechanism and its interaction with the nozzle internal flow are still unclear. However, in recent years synchrotron radiation (SR) X-ray imaging technologies have been widely applied in engine fuel injection studies because of the higher energy and brilliance of third-generation SR light sources. This review provides a brief introduction to the development of SR technology and compares the critical parameters of the primary third-generation SR light sources available worldwide. The basic principles and applications of various X-ray imaging technologies with regard to nozzle internal structure measurements, visualization of in-nozzle flow characteristics and quantitative analyses of near-field spray transient dynamics are examined in detail.

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41. Experimental and Numerical Study of Cervical Muscle Contraction in Frontal Impact

Zhenhai Gao, Zhao Li, Hongyu Hu, Fei Gao

Automotive Innovation 2019, 2 (2): 93-101. DOI: 10.1007/s42154-019-00060-6

摘要（87）

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In a crash situation, drivers typically make evasive maneuvers before an upcoming impact, which can affect the kinematics and injury during impact. The purpose of the current study was to investigate the response and effect of drivers’ cervical muscles in a frontal impact. A crash scenario was developed using a vehicle driving simulator, and 10 volunteers were employed to drive the simulator at 20 km/h, 50 km/h, 80 km/h and 100 km/h. Electromyography (EMG) was recorded from the sternocleidomastoideus (SCM), splenius cervicis (SPL) and trapezium (TRP) muscles using a data acquisition system, and the level of muscle activation was calculated. A numerical study was conducted using data collected in the experiment. The results revealed that the cervical muscles were activated during drivers’ protective action. EMG activity of cervical muscles before impact was greater than that during normal driving. EMG activity increased with driving speed, with the SCM and TRP exhibiting larger increases than the SPL. The kinematics and load of the driver were influenced by muscle activation. Before the collision, the head of an active model stretched backward, while the passive model kept the head upright. In low-speed impact, the torque and shear of the cervical muscle in the active model were much lower than those in the passive model, while the tension of the cervical muscle was higher in the active model compared with the passive model. The results indicated that the incidence of cervical injury in high-speed impact is complex.

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42. Integrated Spacing Policy Considering Micro- and Macroscopic Characteristics

Xinjie Zhang, Yiqing Huang, Konghui Guo, Tao Peng, Shengli Sun, Wentao Li

Automotive Innovation 2019, 2 (2): 102-109. DOI: 10.1007/s42154-019-00049-1

摘要（62）

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An appropriate spacing policy improves traffic flow and traffic efficiency while reducing commuting time and energy consumption. In this paper, the integrated spacing policy that combines the benefits of the constant time headway (CTH) and safety distance (SD) spacing policies is proposed in an attempt to improve traffic flow and efficiency. Firstly, the performance of the CTH and SD spacing policies is analyzed from the perspective of the microscopic characteristics of human-vehicle and the macroscopic characteristics of traffic flow. The switching law between CTH and SD spacing policies and the integrated spacing policy are then proposed to increase traffic efficiency according to the traffic conditions, and the critical speed for the proposed integrated spacing policy is derived. Using the proposed switching law, the integrated spacing policy utilizes the safety redundancy difference between the CTH and SD spacing policies in a flexible manner. Simulation tests demonstrate that the proposed integrated spacing policy increases traffic flow and that the traffic flow maintains string stability in a wider range of traffic flow density.

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43. Concept Study of a Self-localization System for Snow-Covered Roads Using a Four-Layer Laser Scanner

Tetsushi Mimuro, Naoya Taniguchi, Hiroyuki Takanashi

Automotive Innovation 2019, 2 (2): 110-120. DOI: 10.1007/s42154-019-00061-5

摘要（59）

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Many advanced driver assistance systems have entered the market, and automated driving technologies have been developed. Many of them may not work in adverse weather conditions. A forward-looking camera, for example, is the most popular system used for lane det ection but does not work for a snow-covered road. The present paper proposes a self-localization system for snowy roads when the roadsides are covered with snow. The system employs a four-layer laser scanner and onboard sensors and uses only pre-existing roadside snow poles provided for drivers in a snowy region without any other road infrastructure. Because the landscape greatly changes in a short time during a snowstorm and snow removal works, it is necessary to restrict the landmarks used for self-localization to tall objects, like snow poles. A system incorporating this technology will support a driver’s efforts to keep to a lane even in a heavy snowstorm.

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44. Driving-Cycle-Aware Energy Management of Hybrid Electric Vehicles Using a Three-Dimensional Markov Chain Model

Bolin Zhao, Chen Lv, Theo Hofman

Automotive Innovation 2019, 2 (2): 146-156. DOI: 10.1007/s42154-019-00059-z

摘要（58）

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This study developed a new online driving cycle prediction method for hybrid electric vehicles based on a three-dimensional stochastic Markov chain model and applied the method to a driving-cycle-aware energy management strategy. The impacts of different prediction time lengths on driving cycle generation were explored. The results indicate that the original driving cycle is compressed by 50%, which significantly reduces the computational burden while having only a slight effect on the prediction performance. The developed driving cycle prediction method was implemented in a real-time energy management algorithm with a hybrid electric vehicle powertrain model, and the model was verified by simulation using two different testing scenarios. The testing results demonstrate that the developed driving cycle prediction method is able to efficiently predict future driving tasks, and it can be successfully used for the energy management of hybrid electric vehicles.

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